Using the Web to validate document recognition results : Experiments with business cards
Identifieur interne : 001363 ( Main/Exploration ); précédent : 001362; suivant : 001364Using the Web to validate document recognition results : Experiments with business cards
Auteurs : Clemens Oertel [Allemagne] ; Shauna O'Shea [Canada] ; Adam Bodnar [Canada] ; Dorothea Blostein [Canada]Source :
- SPIE proceedings series [ 1017-2653 ] ; 2005.
Descripteurs français
- Pascal (Inist)
English descriptors
- KwdEn :
Abstract
The World Wide Web is a vast information resource which can be useful for validating the results produced by document recognizers. Three computational steps are involved, all of them challenging: (1) use the recognition results in a Web search to retrieve Web pages that contain information similar to that in the document, (2) identify the relevant portions of the retrieved Web pages, and (3) analyze these relevant portions to determine what corrections (if any) should be made to the recognition result. We have conducted exploratory implementations of steps (1) and (2) in the business-card domain: we use fields of the business card to retrieve Web pages and identify the most relevant portions of those Web pages. In some cases, this information appears suitable for correcting OCR errors in the business card fields. In other cases, the approach fails due to stale information: when business cards are several years old and the business-card holder has changed jobs, then websites (such as the home page or company website) no longer contain information matching that on the business card. Our exploratory results indicate that in some domains it may be possible to develop effective means of querying the Web with recognition results, and to use this information to correct the recognition results and/or detect that the information is stale.
Affiliations:
Links toward previous steps (curation, corpus...)
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Le document en format XML
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Computer Science University of British Columbia</wicri:noRegion></affiliation></author><author><name sortKey="Blostein, Dorothea" sort="Blostein, Dorothea" uniqKey="Blostein D" first="Dorothea" last="Blostein">Dorothea Blostein</name><affiliation wicri:level="1"><inist:fA14 i1="02"><s1>School of Computing Queen's University</s1><s2>Kingston, Ontario</s2><s3>CAN</s3><sZ>2 aut.</sZ><sZ>4 aut.</sZ></inist:fA14><country>Canada</country><wicri:noRegion>School of Computing Queen's University</wicri:noRegion></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">INIST</idno><idno type="inist">05-0360301</idno><date when="2005">2005</date><idno type="stanalyst">PASCAL 05-0360301 INIST</idno><idno type="RBID">Pascal:05-0360301</idno><idno type="wicri:Area/PascalFrancis/Corpus">000460</idno><idno type="wicri:Area/PascalFrancis/Curation">000328</idno><idno type="wicri:Area/PascalFrancis/Checkpoint">000369</idno><idno type="wicri:doubleKey">1017-2653:2005:Oertel C:using:the:web</idno><idno type="wicri:Area/Main/Merge">001399</idno><idno type="wicri:Area/Main/Curation">001363</idno><idno type="wicri:Area/Main/Exploration">001363</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en" level="a">Using the Web to validate document recognition results : Experiments with business cards</title><author><name sortKey="Oertel, Clemens" sort="Oertel, Clemens" uniqKey="Oertel C" first="Clemens" last="Oertel">Clemens Oertel</name><affiliation wicri:level="1"><inist:fA14 i1="01"><s1>Bioinformatics, Computer and Cognitive Science University of Tübingen</s1><s3>DEU</s3><sZ>1 aut.</sZ></inist:fA14><country>Allemagne</country><wicri:noRegion>Computer and Cognitive Science University of Tübingen</wicri:noRegion><wicri:noRegion>Bioinformatics, Computer and Cognitive Science University of Tübingen</wicri:noRegion></affiliation></author><author><name sortKey="O Shea, Shauna" sort="O Shea, Shauna" uniqKey="O Shea S" first="Shauna" last="O'Shea">Shauna O'Shea</name><affiliation wicri:level="1"><inist:fA14 i1="02"><s1>School of Computing Queen's University</s1><s2>Kingston, Ontario</s2><s3>CAN</s3><sZ>2 aut.</sZ><sZ>4 aut.</sZ></inist:fA14><country>Canada</country><wicri:noRegion>School of Computing Queen's University</wicri:noRegion></affiliation></author><author><name sortKey="Bodnar, Adam" sort="Bodnar, Adam" uniqKey="Bodnar A" first="Adam" last="Bodnar">Adam Bodnar</name><affiliation wicri:level="1"><inist:fA14 i1="03"><s1>Dept. Computer Science University of British Columbia</s1><s2>Vancouver, BC</s2><s3>CAN</s3><sZ>3 aut.</sZ></inist:fA14><country>Canada</country><wicri:noRegion>Dept. Computer Science University of British Columbia</wicri:noRegion></affiliation></author><author><name sortKey="Blostein, Dorothea" sort="Blostein, Dorothea" uniqKey="Blostein D" first="Dorothea" last="Blostein">Dorothea Blostein</name><affiliation wicri:level="1"><inist:fA14 i1="02"><s1>School of Computing Queen's University</s1><s2>Kingston, Ontario</s2><s3>CAN</s3><sZ>2 aut.</sZ><sZ>4 aut.</sZ></inist:fA14><country>Canada</country><wicri:noRegion>School of Computing Queen's University</wicri:noRegion></affiliation></author></analytic><series><title level="j" type="main">SPIE proceedings series</title><idno type="ISSN">1017-2653</idno><imprint><date when="2005">2005</date></imprint></series></biblStruct></sourceDesc><seriesStmt><title level="j" type="main">SPIE proceedings series</title><idno type="ISSN">1017-2653</idno></seriesStmt></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Error correction</term><term>Information retrieval</term><term>Optical character recognition</term><term>Validation</term><term>World wide web</term></keywords><keywords scheme="Pascal" xml:lang="fr"><term>Réseau web</term><term>Correction erreur</term><term>Reconnaissance optique caractère</term><term>Validation</term><term>Recherche information</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">The World Wide Web is a vast information resource which can be useful for validating the results produced by document recognizers. Three computational steps are involved, all of them challenging: (1) use the recognition results in a Web search to retrieve Web pages that contain information similar to that in the document, (2) identify the relevant portions of the retrieved Web pages, and (3) analyze these relevant portions to determine what corrections (if any) should be made to the recognition result. We have conducted exploratory implementations of steps (1) and (2) in the business-card domain: we use fields of the business card to retrieve Web pages and identify the most relevant portions of those Web pages. In some cases, this information appears suitable for correcting OCR errors in the business card fields. In other cases, the approach fails due to stale information: when business cards are several years old and the business-card holder has changed jobs, then websites (such as the home page or company website) no longer contain information matching that on the business card. Our exploratory results indicate that in some domains it may be possible to develop effective means of querying the Web with recognition results, and to use this information to correct the recognition results and/or detect that the information is stale.</div></front></TEI><affiliations><list><country><li>Allemagne</li><li>Canada</li></country></list><tree><country name="Allemagne"><noRegion><name sortKey="Oertel, Clemens" sort="Oertel, Clemens" uniqKey="Oertel C" first="Clemens" last="Oertel">Clemens Oertel</name></noRegion></country><country name="Canada"><noRegion><name sortKey="O Shea, Shauna" sort="O Shea, Shauna" uniqKey="O Shea S" first="Shauna" last="O'Shea">Shauna O'Shea</name></noRegion><name sortKey="Blostein, Dorothea" sort="Blostein, Dorothea" uniqKey="Blostein D" first="Dorothea" last="Blostein">Dorothea Blostein</name><name sortKey="Bodnar, Adam" sort="Bodnar, Adam" uniqKey="Bodnar A" first="Adam" last="Bodnar">Adam Bodnar</name></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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